Training of Classifiers Using Virtual Samples Only

Authors:
Annika Kuhl;Lars Kruger;Christian Wohler;Ulrich Kresel
Affiliations:
DaimlerChrysler AG Research and Technology, Germany;DaimlerChrysler AG Research and Technology, Germany;DaimlerChrysler AG Research and Technology, Germany;DaimlerChrysler AG Research and Technology, Germany
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Year:
2004

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Abstract

This paper describes the training of classifiers entirely based on virtual images, rendered by a ray-tracing software. Two classifers, a support vector machine and a polynomial classifier, are trained solely with virtual samples and used for classification of real samples.The objects to be distinguished are holes vs. garbage (non-holes) out of a set of hole candidates in images of flanges.We analysed the effect of different classifier parameters and manipulation of the virtual samples.Error rates of 1.6% on real test samples are achieved.